
In addition, we adopt the idea of query expansion [1]}, [2]}, [3]} to further improve its reliability.
Specifically, \(\tilde{w}_{ij}^C\)  is reformulated as the average of the contextual similarities between \(x_j\)  and nearest neighbors of \(x_i\)  as follows:
\(\hat{w}_{ij}^C = \frac{1}{|N_{\frac{k}{2}}(i)|}\sum _{h \in N_{\frac{k}{2}}(i)} \tilde{w}_{hj}^C.\) 
